Associating emotions with Wagner’s music: A developmental perspective
Bibliographic record
Abstract
Brazilian listeners ( N = 303) were asked to identify emotions conveyed in 1-min instrumental excerpts from Wagner’s operas. Participants included musically untrained 7- to 10-year-olds and university students in music (musicians) or science (nonmusicians). After hearing each of eight different excerpts, listeners made a forced-choice judgment about which of eight emotions best matched the excerpt. The excerpts and emotions were chosen so that two were in each of four quadrants in two-dimensional space as defined by arousal and valence. Listeners of all ages performed at above-chance levels, which means that complex, unfamiliar musical materials from a different century and culture are nevertheless meaningful for young children. In fact, children performed similarly to adult nonmusicians. There was age-related improvement among children, however, and adult musicians performed best of all. As in previous research that used simpler musical excerpts, effects due to age and music training were due primarily to improvements in selecting the appropriate valence. That is, even 10-year-olds with no music training were as likely as adult musicians to match a high- or low-arousal excerpt with a high- or low-arousal emotion, respectively. Performance was independent of general cognitive ability as measured by academic achievement but correlated positively with basic pitch-perception skills.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".